A system that fails… every 29 hours
Some infrastructure problems do not appear immediately.
They surface hours or days later, often without an obvious connection to the original change.
These delayed failures can be difficult to diagnose, especially when they involve interactions between multiple system layers.
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The situation
In one environment, an online travel platform experienced recurring performance issues following deployments.
The pattern was consistent:
- shortly after deployment, everything worked normally
- after a little more than a day, the system became slow
- support teams received complaints from sales
- after some time, the system recovered
This cycle repeated itself after each deployment.
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The pattern
Instead of focusing on configuration details, the behavior was analyzed over time.
A key observation emerged:
> the issue always occurred after approximately 29 hours
This timing turned out to be critical.
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What was actually happening
The application environment used Microsoft application servers with a default behavior:
> application pools restart every 29 hours
When these restarts occurred:
- application layers lost their in-memory state
- large volumes of data needed to be reloaded into cache
- the database received a sudden spike of requests
- queries began to time out
- retries increased the load further
This created a feedback loop:
> cache miss → database query → timeout → retry → more load
The system required between 60 and 90 minutes to stabilize.
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Why this was difficult to diagnose
The issue was not caused by:
- a specific deployment error
- a failing component
- a resource limitation
Instead, it was caused by:
> perfectly functioning systems behaving in a synchronized way
All application instances restarted at the same time, creating a coordinated spike in load.
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The fix
The solution was straightforward once the underlying pattern was understood.
The restart intervals were adjusted so that application instances did not restart simultaneously.
This ensured that:
- cache warm-up was distributed over time
- database load remained stable
- no large spikes were introduced
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The result
After staggering the restart intervals:
- the recurring performance degradation disappeared
- database load became predictable
- cache behavior stabilized
The system no longer experienced periodic slowdowns after deployment.
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The lesson
Infrastructure issues are not always caused by failures.
They are often caused by:
- default behaviors
- implicit assumptions
- synchronized system activity
Understanding these patterns requires looking beyond individual components and analyzing how systems interact over time.
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Closing thought
If your platform shows recurring performance issues without an obvious cause, the root problem may lie in how system components interact rather than in any single component.
A structured infrastructure assessment can help uncover these patterns and define practical solutions.